LIVE WEBINAR - About 90 MINUTES

Logistic Regression with Python - A Crash Course

Hosted by
D
David Langer
July 26th | 11:00 am MDT | Show in my timezone

Broadcast has ended.

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Be a Part of the Data-Driven Future of Business

Is data shaping the future of your profession?

While data has always been used in business, things have changed. Functions like HR, Product Management, Customer Service, etc. are embracing analytics to drive better business outcomes.

Do you want to be a part of this data-driven future?

Logistic regression is valuable to ANY professional. Logistic regression allows you to craft predictive models to understand the "why" of what's happening in the business.

Want a crash course in logistic regression?

In about 90 minutes, you will learn to craft logistic regression models using Python. NOTE - This is a purely intuitive introduction. No math background is required!

Are you new to Python?

This webinar assumes a basic level of Python skills. Webinar attendees will get an exclusive discount code for Dave's online Python Quick Start tutorial offered in partnership with TDWI.

Get your questions answered

Dave will answer your questions live during the webinar. A recording of the webinar will be available for 14 days.

Get the files

Attendees will receive an email with a PDF of all slides, a Jupyter Notebook of Python code, and the CSV file used during the webinar.

about

About Dave Langer

Dave Langer founded Dave on Data, where he crafts and delivers training designed for ANY professional to develop valuable data analysis skills. Dave's vision is a world where data analysis skills are as common as skills with Microsoft Office.


Dave has successfully trained 100s of professionals in a live classroom setting and 1000s more via his online courses and tutorials. Dave is a hands-on analytics artisan, combining Excel, SQL, and R/Python to deliver insights that drove business strategy at companies like Schedulicity, Data Science Dojo, and Microsoft.


Dave holds a BA in economics and an MS in computer science from the University of Washington.

July
26
Wednesday
July 26th
11:00 am MDT